code: def setup_method(self):
      self.cases = []
  
      def make_cases(dtype):
          self.cases.append(matrix([[1, 2, 3], [4, 5, 6]], dtype=dtype))
          self.cases.append(
              np.array([[1, 2, 3], [4, 5, 6]], dtype=dtype)
          )
          self.cases.append(
              sparse.csr_matrix([[1, 2, 3], [4, 5, 6]], dtype=dtype)
          )
  
          # Test default implementations of _adjoint and _rmatvec, which
          # refer to each other.
          def mv(x, dtype):
              y = np.array(
                  [
                      1 * x[0] + 2 * x[1] + 3 * x[2],
                      4 * x[0] + 5 * x[1] + 6 * x[2],
                  ],
                  dtype=dtype,
              )
              if len(x.shape) == 2:
                  y = y.reshape(-1, 1)
              return y
  
          def rmv(x, dtype):
              return np.array(
                  [
                      1 * x[0] + 4 * x[1],
                      2 * x[0] + 5 * x[1],
                      3 * x[0] + 6 * x[1],
                  ],
                  dtype=dtype,
              )
  
          class BaseMatlike(interface.LinearOperator):
              def __init__(self, dtype):
                  self.dtype = np.dtype(dtype)
                  self.shape = (2, 3)
  
              def _matvec(self, x):
                  return mv(x, self.dtype)
  
          class HasRmatvec(BaseMatlike):
              def _rmatvec(self, x):
                  return rmv(x, self.dtype)
  
          class HasAdjoint(BaseMatlike):
              def _adjoint(self):
                  shape = self.shape[1], self.shape[0]
                  matvec = partial(rmv, dtype=self.dtype)
                  rmatvec = partial(mv, dtype=self.dtype)
                  return interface.LinearOperator(
                      matvec=matvec,
                      rmatvec=rmatvec,
                      dtype=self.dtype,
                      shape=shape,
                  )
  
          self.cases.append(HasRmatvec(dtype))
          self.cases.append(HasAdjoint(dtype))
  
      make_cases("int32")
      make_cases("float32")
      make_cases("float64")
  
imports: from __future__ import division, print_function, absolute_import
  from functools import partial
  from itertools import product
  import operator
  import pytest
  from pytest import raises, warns
  from numpy.testing import assert_, assert_equal
  import numpy
  import scipy.sparse
  from scipy.sparse.linalg import interface
  from scipy.sparse.sputils import matrix
label_desc: Use image node_id 1 for calling the TestAsLinearOperator obj's underlying member method code with example usage: obj.setup_method() and returns: y, np, mv, rmv, interface